1. Project Summary

Our project focused on job recommendation according to four interesting picked factors, arrival time for work, location, working hours and commuting means. We investigated their effects on income respectively and help make job-decision for your reference. Thus, our team dig into the relations between following factors:

2. Arrival Time vs. Occupation

2.1 Arrival Time vs. Occupation

From this plot, we can see arrival time is different due to many choice of occupations. Most of occupations have arrival time focus on 4-12. Think about the occupation EAT, like chefs or waiters, they have their work time beginning after noon. And it not to understand for that fact.

2.2 Arrival Time vs. States

We can see clearly from the plot that most of people in most of the state arrive at work at 4-8, but In DC, unexpectedly, most of people arrive at 8-12. So basically, if you want to sleep more and get to work late, you can choose DC as your ideal place to work.

2.3 Arrival Time vs. States/Occupation in Bubble Plots

And this Fig is another proof that DC is a good place for work, since it shows that the people work in DC have latest arriving time and highest income. So in my opinion, I suggest DC as a great state to find jobs

As we have mentioned, although EAT has latest arriving time, it also at a low level for salary. Meanwhile, people work as LGL, like lawyers or judges, they earn more but work earlier than others. So we need to make a choice, high salary or get up late?

4. Location vs. Occupation

3.1 Occupation Overview by US States

The following table shows the top and lowest 10 states with highest total number of people taking the survey per state, and their top three frequently mentioned occupations per state.

Top 5 populated states (OCCP):

State Top #1 Top #2 Top #3
CA MGR-Miscellaneous Managers 1.7% SAL-Retail Salesperson 1.5% SAL-Cashiers 1.3%
TX EDU-Elementry and Middle-school Teachers 1.9% MGR-Miscellaneous Managers 1.6% SAL-Cashiers 1.5%
NY EDU-Elementry and Middle-school Teachers 1.7% OFF-Secretaries and Adm Assitants 1.7% SAL-Retail Salesperson 1.5%
FL SAL-Retail Salesperson 1.7% MGR-Miscellaneous Managers 1.7% EDU-Elementry and Middle-school Teachers 1.5%
PA OFF-Secretaries and Adm Assitants 1.7% TRN-Drivers/Sales Workers 1.6% SAL-Cashiers 1.5%

From the above tables, we can conclude that: Top populated states sharing majority of top frequently occupied occupations, such as Miscellanrous Managers, Sales, Cashiers, Elementry and Middle-school Teachers, Secretaries and Assistants, Drivers and Related-sales, and all occpuation’s corresponding percentages are all below 2.0%, which implies

  1. People in high-population states can have more occupation options, thus each occupation percentage is comparatively (to small-scale states) smaller.

  2. The larger-population states do not have a specific focus during state-building process; in other words, they focus on different fields of states’ improvement process instead of one or two specific industries or fields.

Lowest 5 populated states (OCCP):

State Top #1 Top #2 Top #3
WY TRN-Drivers/Sales Workers 2.2% EDU-Elementry and Middle-school Teachers 2% OFF-Secretaries and Adm Assitants 2%
VT EDU-Elementry and Middle-school Teachers 1.8% MGR-Miscellaneous Managers 1.7% SAL-Retail Salesperson 1.6%
DC MGR-Miscellaneous Managers 4.2% LGL-Lawyers, Judges, Magistrates and Other Judicial Workers 3.3% OFF-Secretaries and Adm Assitants 1.7%
AK CLN-Janitros and Building Cleaners 2% MGR-Miscellaneous Managers 1.9% FFF-Fishing and Hunting Workers 1.8%
ND MGR-Farmers, and Other Agricultural Managers 4.4% TRN-Drivers/Sales Workers 2.3% FFF-Miscellaneous Agricultural Workers 1.8%

From the above tables, we can conclude that: most of the low populated states have their own specific focus on states’ industry/occupation fields. For example, in DC, the two of the top three occupations are both related to government and law, while in ND, top three occupations are more related to agriculture. From this fact, we can demonstrate that

  1. People in low-population states may have less occupation options, thus each occupation percentage is comparatively (to large-scale states) greater.

  2. People in low-population states can have more focused industry and fields during state-building process.

3.2 Average Income Performance Overview by Locations

From the above plots, we can tell that (regardless of occupation or industry) * 1st-teir Average Income States: CT, NJ, MD, DC (all on the eastside of US, and comparatively smaller population) * 2nd-teir Average Income States: CA, WA, CO, VA, NY, NH (majority are on both east/west sides of US, and comparatively larger population) * 3rd-teir Average Income States: TX, ND, IL and lower-tiers states are mostly from inland US.

3.4 Overage Income Performance Overview by Occupations

From the above plots, we can tell that law-related, engineering-related, finance-related, and business-related are the top 4 income occupations.

3.5 Job Recommendation based on Locations

  • People who do not have specific focus on their career paths should consider living and working in some high-population states, such as CA, TX, NY, etc.
  • People with specific interests in some industries and focus in their career path, they should consider living and working in some low-population states with specific industry environment, such as lawyers in DC and farmers in ND, etc.
  • People pursue higher income should consider living in the states such as CT, NJ, MD, DC, and choosing the occupations related to Law, Engineering, Finance or Business.

4. Transportation vs. Occupation

From the above heatmap, we can easily find the prefrered occupation for each means of transportation to work. for example, for Taxicab, the deepest blue grid is LGL(LAWYERS, AND JUDGES, MAGISTRATES, AND OTHER JUDICIAL WORKERS), thus the LGL is the best occupation for people who use Taxicab to commute.

The above treemap has been divided into 12 large grids. The 12 large grids represent the means of transportation to work. Each large grid contains some small grids which represent occupation; the size of each small grid is median income of that specific occupation. The color represents the median travel time; the darker the color, the less median time is needed for transportation to work.

5. Working Hours vs. Occupation

5.1 (Ungrouped) Working Hours by Occupations

So the occupation with longest average working hour is Derrick and Mining Machine worker, followed by Military and Lawyer.

On the country, people working in restaurant works least such as cooks or food servers or dishwashers. Then comes people from other service industry, such as Fitness workers, Tour guides, Barbers, etc.

5.2 (Ungrouped) Working Hours, Occupation, vs Income

We can see after working hours exceed 60 hours, the income starts to decrease while working hour keep increasing.

5.3 Grouped Working Hours

So the income is increasing with the working hours when you do not work so much, but as the working hours exceed 60 hours per week, the trend becomes unclear.

Also the trend of different occupation differs a lot. For example, for LGL-LAWYERS, AND JUDGES, MAGISTRATES, AND OTHER, it is increasing all the time, while for people work in medical area such as PHYSICIANS AND SURGEONS, the income is going down as working hours going up, this phenomenon also appears on many other occupations.

If you prefer regular working hour as 8 hours per day or 40 per week, then the top 5 choices of career are Lawyer, Computer programmer or developer, Engineer, Physician and Scientist.

If you are fine with long working hours, you can try to be a Lawyer or Derrick and Mining Machine worker.

Also, It seems that the higher-income jobs do not need you to work overtime while you need to work overtime with low-income job to earn higher income.

6. Conclusion

7. Team Member and Responsibilities: